Book Recommendation System Development Using User-Based Collaborative Filtering

Abstract

In general, a library has a Book Search System, both search books by title, author, publisher, and book subject. But with so many book search results displayed by the system, sometimes it makes users (library members) find it difficult to choose books that match their profile. For that, we need a system that can provide recommendations in the book search process to provide recommendations systematically based on previous user searches. This study aims to produce a book search recommendation system in a desktop-based library using the Python programming language and the MySQL database. recommendation system aims to reduce errors in getting the reference books needed. The information that comes out of the search process is right on target with user needs so that it can streamline time in searching for books. The book search recommendation system uses a user-based collaborative filtering method based on the similarity of one member to another member based on the lending pattern which is grouped based on the subject of the book being sought. This system will display the results of book search recommendations by ranking from highest to lowest and provide book title solutions to users according to their profile. The development of the book search recommendation system uses the System Development life cycle (SDLC) method to design a system with a case study research in the TasikmalayaPejuang University library. The first stage of system development is the Identification of Problems that occur in the University of Struggle library following the phenomena that occur in the field. The second stage is the analysis of software requirements, hardware, and information needed in developing a system. The third stage is the design of workflow system design recommendations for book search using Unified Modeling Language (UML), database design and designing the interface. The fourth stage is the implementation of the design results in real form using Python as a programming language and MySql as a database system. The last step is testing the book search recommendation system using the Blackbox testing method by Trial and Error.